Traditional observation and measurement of physical, chemical, and biological properties of water in coastal and open ocean environments, lakes, rivers, and reservoirs has been carried out primarily by two techniques: 1) sensor devices directly immersed in the water, and 2) research vessels equipped with a plurality of sensing, analysis, and storage capabilities including computers for analysis, processing, and storage of analysis results.
Devices that include predefined sensors to periodically sample water such as drifters and monitoring buoys typically have a reduced lifetime due primarily to two reasons: 1) these systems are sensor-specific and new sensors cannot be easily incorporated without major system modifications involving significant, time consuming, and expensive engineering redesign, and 2) the sensors are immersed and directly exposed in the water which severely affects their useful working life due to the accumulation of organic and inorganic solid materials resulting in sensor malfunctions and unreliable readings within weeks. Consequently, the only way to guarantee reliable readings is to perform periodic maintenance of the buoys on a weekly basis. This requires a time consuming process involving accessing the buoy, collecting all the sensors immersed in water, cleaning the sensors, calibrating the sensors, and re-positioning each sensor at the correct immersion depth. This is a significant limitation since these monitoring buoys may be analyzing waters in locations of difficult access and often it is not possible to perform the scheduled maintenance due to difficult meteorological conditions. Maintenance is even more problematic in systems comprising a several of sensors connected to a line in order to sample water at several different of depths since each submerged sensor must be collected, cleaned, calibrated, and repositioned at the exact depth location.
In addition to the limitations related to the fact that current buoy-based monitoring systems immerse the sensors directly in the water to perform the sampling and the associated maintenance this design requires, other limitations include the maximum depth at which these sensors can be submerged and sample water.
Currently available systems and those disclosed in the art are limited to sampling and sensing close-to-surface-level waters. This limits the type of analytics they can handle and the domain of problems they can be used for.
Consequently, it is desirable to develop water monitoring systems that overcome the above-mentioned limitations and problems.